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arXiv · 2103.02643

Inference for natural mediation effects under case-cohort sampling with applications in identifying COVID-19 vaccine correlates of protection

David Benkeser·Iván Díaz·Jialu Ran
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Abstract

Combating the SARS-CoV2 pandemic will require the fast development of effective preventive vaccines. Regulatory agencies may open accelerated approval pathways for vaccines if an immunological marker can be established as a mediator of a vaccine's protection. A rich source of information for identifying such correlates are large-scale efficacy trials of COVID-19 vaccines, where immune responses are measured subject to a case-cohort sampling design. We propose two approaches to estimation of mediation parameters in the context of case-cohort sampling designs. We establish the theoretical large-sample efficiency of our proposed estimators and evaluate them in a realistic simulation to understand whether they can be employed in the analysis of COVID-19 vaccine efficacy trials.

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David Benkeser, Iván Díaz, Jialu Ran. 2021-03-03. Inference for natural mediation effects under case-cohort sampling with applications in identifying COVID-19 vaccine correlates of protection. https://arxiv.org/abs/2103.02643

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